SBIR-STTR Award

Autonomous Landing of sUAS onto Moving Platforms
Award last edited on: 3/30/2022

Sponsored Program
STTR
Awarding Agency
NSF
Total Award Amount
$1,645,824
Award Phase
2
Solicitation Topic Code
EW
Principal Investigator
Gaemus Collins

Company Information

Planck Aerosystems Inc

710 13th Street Unit 307
San Diego, CA 92101
   (619) 230-5049
   info@planckaero.com
   www.planckaero.com

Research Institution

Brigham Young University

Phase I

Contract Number: 1648563
Start Date: 1/1/2017    Completed: 12/31/2017
Phase I year
2017
Phase I Amount
$224,912
The broader impact/commercial potential of this project is the expansion of autonomous unmanned aerial systems (UAS, or drones) to new maritime operational environments and commercial markets. The proposed technology will enable small UAS to operate from vessels moving at sea, without the need for a dedicated pilot or installed hardware, even while far from shore and beyond the reach of established communication networks. Small UAS can offer the same aerial perspective provided by manned helicopters at a fraction of the size, cost, and risk. Real-time aerial imagery from UAS will supply maritime operators with invaluable information about their surroundings at sea, which is not available by any other means. This information is critical for many maritime applications, including fishing, ocean monitoring, scientific exploration, maritime surveillance, and search, and rescue. This information will offer a particularly large and immediate impact for 98% of worldwide commercial fishing vessels (those that do not carry embarked manned helicopters for fish-finding) by dramatically reducing their fuel costs; providing net economic and environmental gains for the industry.This Small Business Technology Transfer (STTR) Phase I project will develop algorithms and software to enable small UAS autonomously and reliably land onto a moving platform at sea. Commercially-available small UAS can offer invaluable real-time aerial imagery for maritime operators. But, this technology is not currently in widespread use due to technological barriers. In particular, the key enabling technology is the ability to autonomously and reliably land a small UAS onto a moving platform. The research objective is to develop algorithms and software that enable small UAS to autonomously operate from moving vessels at sea. Computer vision algorithms automatically detect the host vessel and the dedicated landing area. Data fusion algorithms estimate the relative drone-boat position and orientation in real time, including compensation for vessel roll, pitch, & heave. Precision control algorithms optimize the drone?s trajectory for save, reliable, autonomous launch and landing. A prototype system will be built by integrating the STTR-developed software with commercially available hardware components.

Phase II

Contract Number: 1758678
Start Date: 3/15/2018    Completed: 2/29/2020
Phase II year
2018
(last award dollars: 2019)
Phase II Amount
$1,420,912

The broader impact/commercial potential of this project will enable Unmanned Aerial Systems(UAS or drones) to safely and reliably operate from moving vehicles and moving vessels at sea.There is an immediate need for this capability in many industries. In commercial fishing, droneswill replace manned aircraft for fish-finding operations, radically reducing cost and risk. In maritimesecurity, drones will provide surveillance around ships, including locating a ?man-overboard? intime to save the person?s life. In the oil and gas industry, drones will provide rapid-response to oilspills by mapping the location and extent of the oil slick, limiting the environmental and economicdamage. In hydrographic surveying, drones will identify and geo-locate navigation aids, at afraction of the time and cost of current survey methods. In commercial shipping, drones willinspect and protect shipping vessels while they are underway. In the transport industry, droneswill delivery packages the ?last mile? from a delivery truck to a customer?s door. In law enforcementand border security, drones will operate from moving patrol vehicles while officers remain safeand mobile in the vehicle. These applications are currently difficult or impossible, but will becomeradically safer and easier with the proposed technology.This Small Business Innovation Research (SBIR) Phase 2 project will advance the current stateof the art in UAS/drone autonomy, to enable reliable drone operations from moving vehicles andmoving vessels at sea. Shipboard landing is extremely difficult, due to the heaving and rolling ofthe ship deck, potential high winds, and the high precision control required during landing. Currentdrone technology does not facilitate landing on moving platforms; this prevents their use inmaritime operations, and has become the main barrier to commercialization in this sector. Theproposed research will develop a vision-aided relative navigation system that combines preciseair-to-ship observations with onboard sensor measurements to accurately estimate the relativestate between the drone and the ship. These relative state estimates will be used to dynamicallyroute and control the drone safely on to the ship deck. Technical feasibility of this approach hasbeen demonstrated during the Phase I project, which included demonstration of the technologyin a relevant environment. The primary goals of the Phase 2 project are to improve systemreliability, expand the operational envelope, and productize our system. The plan to achieve thesegoals includes scientific development paired with extensive testing, validation, and demonstration.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.